code: def binary_xloss(logits, labels, ignore=None):
      """
      Binary Cross entropy loss
        logits: [B, H, W] Variable, logits at each pixel (between -\infty and +\infty)
        labels: [B, H, W] Tensor, binary ground truth masks (0 or 1)
        ignore: void class id
      """
      logits, labels = flatten_binary_scores(logits, labels, ignore)
      loss = StableBCELoss()(logits, Variable(labels.float()))
      return loss
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import torch
  import torch.nn.functional
  from torch import nn
  from torch.autograd import Variable
label_desc: Use image node_id 7 for calling a global function with example usage: binary_xloss(logits, labels, ignore) and returns: loss